| Protopshare: Prototypical parts sharing for similarity discovery in interpretable image classification D Rymarczyk, Ł Struski, J Tabor, B Zieliński Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 121* | 2021 |
| Interpretable image classification with differentiable prototypes assignment D Rymarczyk, Ł Struski, M Górszczak, K Lewandowska, J Tabor, ... European Conference on Computer Vision, 351-368, 2022 | 92 | 2022 |
| Deep learning approach to describe and classify fungi microscopic images B Zieliński, A Sroka-Oleksiak, D Rymarczyk, A Piekarczyk, ... PloS one 15 (6), e0234806, 2020 | 87 | 2020 |
| Kernel self-attention for weakly-supervised image classification using deep multiple instance learning D Rymarczyk, A Borowa, J Tabor, B Zielinski Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 59* | 2021 |
| Protoseg: Interpretable semantic segmentation with prototypical parts M Sacha, D Rymarczyk, Ł Struski, J Tabor, B Zieliński Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 32 | 2023 |
| ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification D Rymarczyk, A Pardyl, J Kraus, A Kaczyńska, M Skomorowski, ... ECML PKDD 2022, 2022 | 32* | 2022 |
| Icicle: Interpretable class incremental continual learning D Rymarczyk, J van de Weijer, B Zieliński, B Twardowski Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 22 | 2023 |
| Deep learning models capture histological disease activity in Crohn’s disease and ulcerative colitis with high fidelity D Rymarczyk, W Schultz, A Borowa, JR Friedman, T Danel, P Branigan, ... Journal of Crohn's and Colitis 18 (4), 604-614, 2024 | 13 | 2024 |
| Interpretability benchmark for evaluating spatial misalignment of prototypical parts explanations M Sacha, B Jura, D Rymarczyk, Ł Struski, J Tabor, B Zieliński Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 21563 …, 2024 | 9 | 2024 |
| Deep learning classification of bacteria clones explained by persistence homology A Borowa, D Rymarczyk, D Ochońska, M Brzychczy-Włoch, B Zieliński 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 9* | 2021 |
| ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging Ł Struski, D Rymarczyk, A Lewicki, R Sabiniewicz, J Tabor, B Zieliński European Conference on Artificial Intelligence, 2210-2217, 2023 | 8 | 2023 |
| Progrest: Prototypical graph regression soft trees for molecular property prediction D Rymarczyk, D Dobrowolski, T Danel Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 3 | 2023 |
| Identifying bacteria species on microscopic polyculture images using deep learning A Borowa, D Rymarczyk, D Ochońska, A Sroka-Oleksiak, ... IEEE Journal of Biomedical and Health Informatics 27 (1), 121-130, 2022 | 3 | 2022 |
| CompLung: Comprehensive Computer-Aided Diagnosis of Lung Cancer A Pardyl, D Rymarczyk, J Jaworek-Korjakowska, D Kucharski, A Brodzicki, ... European Conference on Artificial Intelligence, 1835-1842, 2023 | 2 | 2023 |
| Automating patient-level lung cancer diagnosis in different data regimes A Pardyl, D Rymarczyk, Z Tabor, B Zieliński International Conference on Neural Information Processing, 13-24, 2022 | 2 | 2022 |
| Decoding phenotypic screening: A comparative analysis of image representations A Borowa, D Rymarczyk, M Żyła, M Kańduła, A Sánchez-Fernández, ... Computational and Structural Biotechnology Journal 23, 1181-1188, 2024 | 1 | 2024 |
| Revisiting FunnyBirds evaluation framework for prototypical parts networks S Opłatek, D Rymarczyk, B Zieliński World Conference on Explainable Artificial Intelligence, 57-68, 2024 | 1 | 2024 |
| LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision M Pach, D Rymarczyk, K Lewandowska, J Tabor, B Zieliński arXiv preprint arXiv:2405.14331, 2024 | 1 | 2024 |
| Multimodal Approach to MoA Prediction Based on Cell Painting Imaging and Chemical Structure Data M Koziarski, P Gaiński, K Rataj, A Borowa, K Wójtowicz, J Gwóźdź, ... ELRIG, 2022 | 1 | 2022 |
| Comparison of supervised and self-supervised deep representations trained on histological images D Rymarczyk, A Borowa, A Bracha, M Chronowski, W Ozimek, B Zieliński MEDINFO 2021: One World, One Health–Global Partnership for Digital …, 2022 | 1 | 2022 |
Bartosz M ZielinskiJagiellonian University, IDEAS NCBRZweryfikowany adres z uj.edu.pl
